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Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)

Cell–cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per exp...

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Autores principales: Madrigal, Justin L., Schoepp, Nathan G., Xu, Linfeng, Powell, Codian S., Delley, Cyrille L., Siltanen, Christian A., Danao, Jay, Srinivasan, Maithreyan, Cole, Russell H., Abate, Adam R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812558/
https://www.ncbi.nlm.nih.gov/pubmed/35074872
http://dx.doi.org/10.1073/pnas.2110867119
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author Madrigal, Justin L.
Schoepp, Nathan G.
Xu, Linfeng
Powell, Codian S.
Delley, Cyrille L.
Siltanen, Christian A.
Danao, Jay
Srinivasan, Maithreyan
Cole, Russell H.
Abate, Adam R.
author_facet Madrigal, Justin L.
Schoepp, Nathan G.
Xu, Linfeng
Powell, Codian S.
Delley, Cyrille L.
Siltanen, Christian A.
Danao, Jay
Srinivasan, Maithreyan
Cole, Russell H.
Abate, Adam R.
author_sort Madrigal, Justin L.
collection PubMed
description Cell–cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per experiment; this limited throughput makes it difficult to characterize interactions at biologically relevant scales. Here, we describe a paradigm in cell interaction profiling that allows accurate grouping of cells and characterization of their interactions for tens to hundreds of thousands of combinations. Our approach leverages high-throughput droplet microfluidics to construct multicellular combinations in a deterministic process that allows inclusion of programmed reagent mixtures and beads. The combination droplets are compatible with common manipulation and measurement techniques, including imaging, barcode-based genomics, and sorting. We demonstrate the approach by using it to enrich for chimeric antigen receptor (CAR)-T cells that activate upon incubation with target cells, a bottleneck in the therapeutic T cell engineering pipeline. The speed and control of our approach should enable valuable cell interaction studies.
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spelling pubmed-88125582022-02-16 Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs) Madrigal, Justin L. Schoepp, Nathan G. Xu, Linfeng Powell, Codian S. Delley, Cyrille L. Siltanen, Christian A. Danao, Jay Srinivasan, Maithreyan Cole, Russell H. Abate, Adam R. Proc Natl Acad Sci U S A Biological Sciences Cell–cell interactions are important to numerous biological systems, including tissue microenvironments, the immune system, and cancer. However, current methods for studying cell combinations and interactions are limited in scalability, allowing just hundreds to thousands of multicell assays per experiment; this limited throughput makes it difficult to characterize interactions at biologically relevant scales. Here, we describe a paradigm in cell interaction profiling that allows accurate grouping of cells and characterization of their interactions for tens to hundreds of thousands of combinations. Our approach leverages high-throughput droplet microfluidics to construct multicellular combinations in a deterministic process that allows inclusion of programmed reagent mixtures and beads. The combination droplets are compatible with common manipulation and measurement techniques, including imaging, barcode-based genomics, and sorting. We demonstrate the approach by using it to enrich for chimeric antigen receptor (CAR)-T cells that activate upon incubation with target cells, a bottleneck in the therapeutic T cell engineering pipeline. The speed and control of our approach should enable valuable cell interaction studies. National Academy of Sciences 2022-01-24 2022-02-01 /pmc/articles/PMC8812558/ /pubmed/35074872 http://dx.doi.org/10.1073/pnas.2110867119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Madrigal, Justin L.
Schoepp, Nathan G.
Xu, Linfeng
Powell, Codian S.
Delley, Cyrille L.
Siltanen, Christian A.
Danao, Jay
Srinivasan, Maithreyan
Cole, Russell H.
Abate, Adam R.
Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title_full Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title_fullStr Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title_full_unstemmed Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title_short Characterizing cell interactions at scale with made-to-order droplet ensembles (MODEs)
title_sort characterizing cell interactions at scale with made-to-order droplet ensembles (modes)
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812558/
https://www.ncbi.nlm.nih.gov/pubmed/35074872
http://dx.doi.org/10.1073/pnas.2110867119
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